wilmott.com

why is the code in the paper wrong?could you be more specific?worked fine for me..its not 100% carbon copy,modified to suit my requirements..

oh hello:I am also currently following Moodley's code on SV models. Howver, I found some stragne problem about the characteristic funciton (CF) in his code. The CF looks not exact the same as the one in Heston's paper (1993). However, Moodley's code still give quite good result with the CF derived by Hong (2004) compared with the option-city calculator. Then, I try to replace as Heston's CF (1993) in the code, the code gives me weird result. After careful derivation, I found the two CF (from Heston and Hong) are really different. Does there anyone have same experience? Or anyone can explain why Heston's original CF doen't work in the code????much much appreciated,Marco

Dear all,We have also been working on a stochastic volatility project. We want to calibrate Heston model for fx options.We wanted to use ASA for calibration.Sergei Mikhailov, Ulrich Nögel state in their paper 'Heston’s Stochastic Volatility,Model Implementation,Calibration and Some Extensions' that 'In contrast to the local optimizers the initial guess is (hopefully)irrelevant in the concept of stochastic optimization.' And they use ASA for calibration.When we try to calibrate Heston model with ASA using a data set which consists of 42 options on a spesific day we see that calibration results totaly depend on initial parameters.Further although we get different calibrated values ,these different set ofparameters equally work well,we have very minor errors for each of them.We wonder where the problem is.Can it be something related to number of data points i.e should we take e.g 84 options on that day in stead of 42 options?We want look at the term structure of parameters then how can we achieve this if there are 2 different set of parameters which work equally well for a spesific day.I mean how can we handle with that multiplicity problem?Thank you very much for your help.Best regards,

Hi minimus,just out of curiosity, what't the average time it's taking to calibrate the model with 42 options ? Thanks

QuoteOriginally posted by: mixumusDear all,We have also been working on a stochastic volatility project. We want to calibrate Heston model for fx options.We wanted to use ASA for calibration.Sergei Mikhailov, Ulrich Nögel state in their paper 'Heston’s Stochastic Volatility,Model Implementation,Calibration and Some Extensions' that 'In contrast to the local optimizers the initial guess is (hopefully)irrelevant in the concept of stochastic optimization.' And they use ASA for calibration.When we try to calibrate Heston model with ASA using a data set which consists of 42 options on a spesific day we see that calibration results totaly depend on initial parameters.Further although we get different calibrated values ,these different set ofparameters equally work well,we have very minor errors for each of them.We wonder where the problem is.Can it be something related to number of data points i.e should we take e.g 84 options on that day in stead of 42 options?We want look at the term structure of parameters then how can we achieve this if there are 2 different set of parameters which work equally well for a spesific day.I mean how can we handle with that multiplicity problem?Thank you very much for your help.Best regards,It's a bad idea to try to calibrate stochastic volatility models to a single expiration -- the parameter estimates will belargely meaningless as you have discovered. Get the full option chain and calibrate to that. regards,